The present invention relates generally to the field of medical imaging and more specifically to the evaluation of features of interest in image data acquired using different imaging modalities. In particular, the present invention relates to the evaluation of malignancies observable in computed tomography (CT) and positron emission tomography (PET) image data.
Non-invasive imaging broadly encompasses techniques for generating images of the internal structures or regions of a person that are otherwise inaccessible for visual inspection. One of the best known uses of non-invasive imaging is in the medical arts where these techniques are used to generate images of organs and/or bones inside a patient which would otherwise not be visible. One class of medical non-invasive imaging techniques is based on the generation of structural images of internal structures which depict the physical arrangement, composition, or properties of the imaged region. Example of such modalities include X-ray based techniques, such as CT and tomosynthesis. In these X-ray based techniques, the attenuation of X-rays by the patient is measured at different view angles and this information is used to reconstruct two-dimensional images and/or three-dimensional volumes of the imaged region.
Another modality used to generate structural images is magnetic resonance imaging (MRI). In MRI, the tissues undergoing imaging are subjected to strong magnetic fields and to radio wave perturbations which produce measurable signals as the tissues of the body align and realign themselves based upon their composition. These signals may then be used to reconstruct structural images that reflect the physical arrangement of tissues based on these different gyromagnetic responses. Another example of a structural imaging modality is ultrasound imaging, in which the differential reflection of acoustic waves by the internal structures of a patient is used to reconstruct images of the internal anatomy.
While structural imaging modalities generate images of the physical composition or arrangement of a region of interest, functional imaging modalities generate images reflecting the chemical composition or metabolic activity of the region of interest. Examples, of such functional imaging modalities include nuclear medicine, single-photon emission computed tomography (SPECT), and PET. These modalities typically detect photons or gamma rays, either directly or indirectly, which are generated by a radioactive tracer introduced into the patient. Based on the type of metaboland, sugar, or other compound into which the radioactive tracer is incorporated, the radioactive tracer is accumulated in different parts of the patient and measurement of the resulting gamma rays can be used to localize and image the accumulation of the tracer. For example, tumors may disproportionately utilize glucose or other substrates relative to other tissues such that the tumors may be detected and localized using radioactively tagged deoxyglucose. Other examples of functional imaging modalities include functional MRI, in which chemical composition information is obtained, and fluorescence imaging.
The different functionalities of structural and functional imaging may be combined to provide more information to a diagnostician than either modality alone. For example, in the case of combined PET/CT scanners, a clinician is able to acquire both PET and CT image data that can be used in conjunction to detect tumors or to evaluate the progression of a tumor. In such an example, the clinician typically evaluates different malignancy characteristics that can be measured in each type of image data. In particular, the PET image data provides useful metabolic information, such as the molecular signature of disease, while the CT image data provides useful anatomic and geometric information in the form of high-resolution images and volume renderings. The malignancy characteristics derived from each type of data may then be considered together and utilized to characterize suspicious areas as well as to accurately assess cancer stages.
While the availability and analysis of both functional and structural image data (such as PET and CT images) provides diagnostic opportunities, several challenges to such techniques still exist. For example, in the case of combined PET/CT systems the image data is typically visually inspected by a clinician who provides a subjective assessment based on the visual inspection. However, the presentation of subtle disease state presentations, in either PET or CT image data, may be problematic. For example, a clinician may not know how to quantitatively determine whether a slight increase in a PET signal is due to a benign process or to a malignant process. Proper interpretation of this data typically requires a thorough understanding of the physics processes and image formation techniques involved, which may not be information available to or known by the average practicing clinician. Furthermore, even if this information were known by the clinician, the calculations involved to quantify and assess the significance of a signal change would be too laborious to manually perform on a regular basis.
Furthermore, few clinicians have the knowledge or experience to fully understand and interpret the combined PET and CT data. Typically a clinician is primarily trained in the interpretation of image data from one type of image modality, but not both. Furthermore, synergies exist in the combined PET and CT image data such that the combined data may contain critical information that is not obvious or apparent in the uncombined image data. Apprehension of this synergistic information may not be possible by a clinician trained with respect to only one of the image modalities or inexperienced in the evaluation of such combined image data sets.